Open AccessUncertainty analysis of direct radiative forcing by anthropogenic sulfate aerosols
Author(s) -
Pan Wenwei,
Tatang Menner A.,
McRae Gregory J.,
Prinn Ronald G.
Publication year - 1997
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/97jd01653
Subject(s) - radiative forcing , aerosol , radiative transfer , environmental science , parametric statistics , sulfate aerosol , range (aeronautics) , forcing (mathematics) , uncertainty analysis , sulfate , monte carlo method , probabilistic logic , atmospheric sciences , collocation (remote sensing) , uncertainty quantification , meteorology , mathematics , statistics , physics , chemistry , materials science , remote sensing , geography , organic chemistry , quantum mechanics , composite material
Uncertainty in the direct radiative forcing by anthropogenic sulfate aerosols is analyzed for four different aerosol model structures with 13 uncertain parameters using a second‐order probabilistic collocation method. The resulting probability density functions agree well with those determined here by a computationally much more expensive 10,000‐point Monte Carlo method. The structural difference, measured by the range of the mean responses in models with different approximations, is −0.28 to −1.3 W m −2 , and the parametric uncertainty, induced by the uncertainties in the model parameters, is −0.1 to −4.2 W m −2 , both with 95% confidence. This implies that refining uncertain input parameters may be more important than improving models in order to minimize the overall uncertainty in the direct radiative forcing by anthropogenic sulfate aerosols in these four models. The variance analysis indicates that the parametric uncertainty comes mainly from sulfate yield, sulfate lifetime, and ambient relative humidity. Variance contributions from aerosol size parameters are much smaller, and this finding agrees with the sensitivity analysis by Boucher and Anderson [1995]. Note that the conclusions reached here are dependent on the chosen model structures and parameter distributions. This study presents a computationally efficient framework for assessing uncertainty in aerosol radiative forcing which could be used to address an even wider range of structures and parameters in the future.